2型糖尿病患者血糖波动指标与MAU的相关性
| 作者: |
1白倩,
1陈琰,
1代闪,
1王彦君
1 吉林大学第二医院内分泌科，长春 130041 |
| 通讯: |
王彦君
Email: jdeywyj1966@126.com |
| DOI: | 10.3978/j.issn.2095-6959.2019.08.014 |
| 基金: | 吉林省卫生与计划生育委员会青年骨干项目(2017Q030)。 |
摘要
目的：探讨2型糖尿病患者尿微量白蛋白(microalbunminuria，MAU)与动态血糖监测参数中的变异系数(variable coefficient，CV)、日平均血糖波动幅度(mean amplitude of glycemic excursions，MAGE)及葡萄糖范围内时间(time in range，TIR)的相关性。方法：106例2型糖尿病患者根据MAU结果分为两组，<30 mg者为对照组(A组)(53例)，≥30 mg为研究组(B组)(53例)，采集患者的一般资料，主要包括空腹血糖(fasting blood-glucose，FPG)、糖化血红蛋白(HbA1c)、收缩压(systolic blood pressure，SBP)、舒张压(diastolic blood pressure，DBP)，同时所有入组患者均采用72 h动态血糖监测系统(continuous glucose monito-ring system，CGMS)评估血糖变异性，记录平均血糖(mean blood glucose，MBG)，平均血糖标准差(standard deviation of mean blood glucose，SDBG)，CV，MAGE，最大血糖波动幅度(large amplitude of glycemic excursions，LAGE)，TIR；MAU与血糖波动的相关性采用Pearson相关分析及多元逐步回归分析进行评估。结果：两组之间单因素分析结果显示：B组HbA1c，SBP，MBG，SDBG，CV，MAGE，LAGE均高于A组，TIR低于A组(P<0.05)；Pearson相关分析显示：B组患者的MAU水平与TIR水平呈负相关(r=−0.846)，与SBP，MBG，SDBG，CV，MAGE水平呈正相关(r分别为0.653，0.346，0.271，0.434，0.963，0.967)；多因素回归分析显示：CV，MAGE是MAU升高的独立危险因素，而TIR为保护因素(95%CI：0.601~4.932，1.714~6.439，−0.153~−0.018；P<0.01)。结论：2型糖尿病合并MAU者血糖变异性更大，TIR比例更低，MAGE，CV及TIR可作为临床评估糖尿病肾病(diabetic kidney disease，DKD)的敏感指标，及早干预可明显提高相关人群的生活质量。
关键词：
尿微量白蛋白；动态血糖监测参数；血糖变异系数；日平均血糖波动幅度；葡萄糖范围内时间
Correlations between blood glucose fluctuation indexes and microalbunminuria in patients with type 2 diabetes mellitus
CorrespondingAuthor: WANG Yanjun Email: jdeywyj1966@126.com
DOI: 10.3978/j.issn.2095-6959.2019.08.014
Foundation: This work was supported by the Youth Backbone Project of Jilin Provincial Health and Family Planning Commission, China (2017Q030).
Abstract
Objective: To investigate the correlations between urinary microalbunminuria (MAU) and variable coefficient (CV), daily mean glycemic fluctuation (MAGE) and time in range (TIR) of glucose which are assessed by continuous glucose monitoring (CGM) in patients with type 2 diabetes. Methods: According to the results of MAU, 106 cases of patients with type 2 diabetes is divided into two groups: <30 milligram as a control group (group A) (53 cases), ≥30 milligram as a study group (group B) (53 cases). We gathered the general information of patients, including fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), diastolic blood pressure (DBP). At the same time, all enrolled patients were assessed by 72 h dynamic blood glucose monitoring system (CGMS), and mean blood glucose (MBG), mean blood glucose standard deviation (SDBG), blood glucose variable coefficient (CV), daily mean amplitude of glycemic excursions (MAGE), maximum blood glucose fluctuation amplitude (LAGE), and time in range (TIR) assessed by CGM were recorded, the correlation between MAU and glucose fluctuation was evaluated by Pearson correlation analysis and multiple stepwise regression analysis. Results: The results of univariate analysis between the two groups showed that the HbA1c, SBP, MBG, SDBG, CV, MAGE and LAGE of group B were all higher than group A, and the TIR was lower than group A (P<0.05). Pearson correlation analysis showed that MAU level in group B was negatively correlated with TIR level (r=−0.846) and positively correlated with SBP, MBG, SDBG, CV and MAGE levels (r were 0.653, 0.346, 0.271, 0.434, 0.963, 0.967). Multivariate regression analysis showed that CV and MAGE were independent risk factors for MAU elevation and TIR were protective factors (95%CI: 0.601 to 4.932, 95%CI: 1.714 to 6.439, 95%CI: −0.153 to −0.018; P<0.01). Conclusion: Type 2 diabetes mellitus with MAU has higher blood glucose variability and lower TIR ratio, MAGE, CV and TIR can be used as sensitive indicators for clinical assessment of diabetic nephropathy. Early intervention may significantly improve the quality of life of the relevant population.
Keywords：
urinary microalbumin; continuous glucose monitoring parameters; glucose variation coefficient; daily mean glucose fluctuation amplitude; time in range